Pears | Pears are common patterns of markup & amp ; style | Content Management System library

df1:

I have 2 datasets like this: Fruits

This dataset represents if a person with that ID has that fruit(1) or not(0). Here ID is the primary key.

Another dataset is Juice. This table represents juice made by that ID on the given date. There are no duplicates in this dataset.

My desired output would be to know which fruit was used how many times. If an Id has more than 1 fruit, consider he used both the fruits to make the juice.

Let's follow column-wise- Apples- ID 2, ID 3 and ID 5 has apples. ID 2 made juice 3 times, ID 3 made juice 1 time and ID 3 made juice 1 time, so apple was used 5 times(3+1+1). Similarly, ID 1 and ID 3 has oranges. ID 1 made juice 2 times and ID 3 made juice 1 time, so orange was used 3 times(2+1). ID 1 made juice 2 times, and ID 4 made juice 0 times, so pear was used 2 times.

I want this in R, Python or SQL, though I think R has the best functions to approach this problem. I am not really sure how to approach this as there are two tables involved. Any help would be really appreciated.

I have a table with x num of rows, I have a second table with the same number of rows but different columns and metadata, they have different table models. but each row represents the same object (a song).

I want to synchronize row sorting between the two tables so for example if I sort on column 2 of table 1 then rows of the table will be sorted in the same order. But currently, I just have sorted by matching sort keys so sort on the same column (but because different data get different results)

e.g

Starting point

I have some dataframes I want to plot with a variable number of Fruits. When plotting, each dataframe will always have the same Fruit types, even though some may have a value of 0 in their respective row.

Each day, I get an email with the quantities of fruit sold on a particular day. The structure of the email is as below:

I currently have a table in Power BI named Fruit.

Here is sample data from Fruit:

I have created a table to join the label values into one: AllLabel = SUMMARIZE(UNION(VALUES(Fruit[Label 1]), VALUES(Fruit[Label 2]), VALUES(Fruit[Label 3]), VALUES(Fruit[Label 4])),Fruit[Label 1])

I also have created a measure count the labels and filter them uniquely: Apples Oranges Pears Bananas Strawberries Dragon Fruit Grapes:

I have the following pandas multi-index dataframe and I would like it to become a nested json object.

I have two data frames with string values:

I have created a simple unordered list: